def extract_from_date(from_date_string, to_date_string):
current_date = format_date(from_date_string)
d, m, y = utils.formatted_date(current_date)
if y == 100000:
current_date = format_date(to_date_string)
d, m, y = utils.formatted_date(current_date)
elif not y:
[issue_flag, date_diff] = utils.date_difference(from_date_string,
to_date_string)
if not issue_flag:
last_date = format_date(to_date_string)
ld, lm, ly = utils.formatted_date(last_date)
if ly and ly != 100000:
to_date = ld + lm * 30 + ly * 365 - date_diff
d, m, y = int((to_date % 365) % 12), int(
(to_date % 365) / 12), int(to_date / 365)
return "{},{},{}".format(d, m, y)
def compute_median_career_time(db_utils,
work_meta_info,
min_conf=0,
soc_level=configurator.commons.SOC_LEVEL):
''' Creating an array of work ex index attributes '''
from_index = 1
to_index = 15
title_durations = {}
resume_count = 0
''' Fetching a cursor over all non-duplicate resumes '''
resumes = db_utils.fetch_data("resume", "cursor", {"Duplicate": False})
''' Iterating over the cursor to find the transition times for each title '''
for resume in resumes:
resume_count += 1
if resume_count % 10000 == 0:
print "Processed {} resumes".format(resume_count)
career_start_date = None
for index in list(reversed(range(from_index - 1, to_index))):
''' Check whether the given work experience is a valid one, in case it is we need to do further processing otherwise not '''
current_work_ex_meta_info = work_meta_info[index]
if is_valid_work_experience(resume, current_work_ex_meta_info,
min_conf):
''' This is a valid work experience, we should add the title and the time taken by this person to reach this title '''
current_date = extract_from_date(
resume[current_work_ex_meta_info['from']],
resume[current_work_ex_meta_info['to']])
cy = [int(x) for x in current_date.split(',')][2]
if cy != 100000 and cy:
''' From Date is valid '''
''' Check whether this is the start point in this career '''
if not career_start_date:
''' We have found the career start date '''
career_start_date = current_date
title_tuple = (
resume[current_work_ex_meta_info['title']],
resume[current_work_ex_meta_info['soc']][:soc_level])
if title_tuple not in title_durations:
title_durations[title_tuple] = []
[issue_flag, duration_to_reach
] = utils.date_difference(career_start_date, current_date)
if not issue_flag:
title_durations[title_tuple].append(duration_to_reach)
return title_durations
def create_major_titles_map(work_meta_info, end_title_limit, start_title_limit,
majors, degrees):
major_field = "latest_ed_major"
degree_field = "latest_ed_degree"
latest_ed_from = "latest_ed_from"
latest_ed_to = "latest_ed_to"
resumes = dbutils.fetch_data('resume', 'cursor', {
'latest_ed_major': {
'$in': majors
},
'latest_ed_degree': {
'$in': degrees
}
})
major_title_map = {}
resume_count = 0
for resume in resumes:
degree = norm_degree(resume[degree_field])
date_string = format_date(resume[latest_ed_from])
d, m, y = utils.formatted_date(date_string)
is_valid_date_flag = True
if y == 100000 or not y:
is_valid_date_flag = False
if not is_valid_date_flag:
date_string = format_date(resume[latest_ed_to])
d, m, y = utils.formatted_date(date_string)
is_valid_date_flag = True
if y == 100000 or not y:
is_valid_date_flag = False
if resume[major_field] and degree and is_valid_date_flag:
if resume[major_field] not in major_title_map:
major_title_map[resume[major_field]] = {}
if degree not in major_title_map[resume[major_field]]:
major_title_map[resume[major_field]][degree] = {}
major_title_map[
resume[major_field]][degree]["valid_resumes"] = 0
major_title_map[resume[major_field]][degree]["title_dict"] = {}
major_title_map[resume[major_field]][degree]["valid_resumes"] += 1
total_exp = 0
for work_info_obj in work_meta_info:
if is_valid_work_info(resume, work_info_obj):
date_string = format_date(resume[work_info_obj['to']])
wtd, wtm, wty = utils.formatted_date(date_string)
is_valid_date_flag = True
to_years = 0
from_years = 0
if wty == 100000 or not wty:
is_valid_date_flag = False
else:
to_years += (wtd + wtm * 30 + wty * 12 * 30)
wfy = 0
if not is_valid_date_flag:
date_string = format_date(
resume[work_info_obj['from']])
wfd, wfm, wfy = utils.formatted_date(date_string)
is_valid_date_flag = True
if wfy == 100000 or not wfy:
is_valid_date_flag = False
else:
from_years += (wfd + wfm * 30 + wfy * 12 * 30)
if wfy == 100000 or wty == 100000 or (
is_valid_date_flag and
(to_years > (d + m * 30 + y * 12 * 30) or
(not to_years and from_years >=
(d + m * 30 + y * 12 * 30)))):
[issue_flag, years_of_exp] = utils.date_difference(
resume[work_info_obj["from"]],
resume[work_info_obj["to"]])
if not issue_flag:
if resume[work_info_obj[
"title"]] not in major_title_map[resume[
major_field]][degree]["title_dict"]:
major_title_map[
resume[major_field]][degree]["title_dict"][
resume[work_info_obj["title"]]] = {}
exp = int(total_exp)
if exp not in major_title_map[
resume[major_field]][degree]["title_dict"][
resume[work_info_obj["title"]]]:
major_title_map[resume[major_field]][degree][
"title_dict"][resume[
work_info_obj["title"]]][exp] = 0
major_title_map[
resume[major_field]][degree]["title_dict"][
resume[work_info_obj["title"]]][exp] += 1
total_exp += years_of_exp
resume_count += 1
if resume_count % 10000 == 0:
print "{} Resumes Processed".format(resume_count)
print "{} Resumes Processed".format(resume_count)
return major_title_map
def create_edges_from_resume(resume, work_meta_info, min_conf, edges, nodes,
major):
is_valid_date_flag = True
[d, m, y] = [
int(x)
for x in extract_from_date(resume["latest_ed_from"], resume[
"latest_ed_to"]).split(',')
]
if y == 100000 or not y:
is_valid_date_flag = False
if is_valid_date_flag:
valid_index = False
path = []
title_time_map = {}
for index in reversed(range(1, 15)):
current_work_ex_meta_info = work_meta_info[index]
next_work_ex_meta_info = work_meta_info[index - 1]
if (current_work_ex_meta_info["title"] in resume and
resume[current_work_ex_meta_info["title"]] and
current_work_ex_meta_info["match"] in resume and
resume[current_work_ex_meta_info["match"]] and
current_work_ex_meta_info["confidence"] in resume and
resume[current_work_ex_meta_info["confidence"]] >= min_conf
and next_work_ex_meta_info["title"] in resume and
resume[next_work_ex_meta_info["title"]] and
next_work_ex_meta_info["match"] in resume and
resume[next_work_ex_meta_info["match"]] and
next_work_ex_meta_info["confidence"] in resume and
resume[next_work_ex_meta_info["confidence"]] >= min_conf
and resume[current_work_ex_meta_info["title"]] !=
resume[next_work_ex_meta_info["title"]]):
''' There is a valid edge present from the work experience at index to the one
at (index-1) '''
current_date = extract_from_date(
resume[current_work_ex_meta_info['from']],
resume[current_work_ex_meta_info['to']])
[cd, cm, cy] = [int(x) for x in current_date.split(',')]
if valid_index or (d + m * 30 + y * 365) <= (
cd + cm * 30 + cy * 365):
from_title = resume[current_work_ex_meta_info["title"]]
to_title = resume[next_work_ex_meta_info["title"]]
if not valid_index:
valid_index = True
path.append(from_title)
title_time_map[from_title] = current_date
path.append(to_title)
edge = (from_title, to_title)
if edge not in edges:
edges[edge] = {}
edges[edge]['count'] = 0
edges[edge]['time_intervals'] = []
if from_title not in nodes:
nodes.add(from_title)
if to_title not in nodes:
nodes.add(to_title)
edges[edge]['count'] += 1
next_date = extract_from_date(
resume[next_work_ex_meta_info['from']],
resume[next_work_ex_meta_info['to']])
title_time_map[to_title] = next_date
[issue_flag, date_diff] = utils.date_difference(
current_date, next_date)
if not issue_flag:
edges[edge]['time_intervals'].append(date_diff)
for i, node1 in enumerate(path):
current_date = title_time_map[
node1] if node1 in title_time_map else ''
for j, node2 in enumerate(path[i + 2:]):
edge = (node1, node2)
if edge not in edges:
edges[edge] = {}
edges[edge]['count'] = 0
edges[edge]['time_intervals'] = []
edges[edge]['count'] += 1 / (j + 2)
next_date = title_time_map[
node2] if node2 in title_time_map else ''
if current_date and next_date:
[issue_flag, date_diff] = utils.date_difference(
current_date, next_date)
if not issue_flag:
edges[edge]['time_intervals'].append(date_diff)
def run(self):
home_dir = pathlib.Path.home()
desktop = os.path.expanduser('~/Desktop/output.csv')
filename = qtw.QFileDialog.getSaveFileName(self, 'Save File', desktop)
n_rows = self.ui.rate_changes_table.rowCount()
rate_change_list = []
previous_date = self.ui.date_input.date().toPyDate()
rate_value = float(self.ui.initial_interest_input.text()) / (100 * 12)
total_months = 0
for i in range(n_rows):
change_date = self.ui.rate_changes_table.item(i, 0)
change_rate = self.ui.rate_changes_table.item(i, 1)
if change_date is not None and change_rate is not None:
change_date_value = datetime.strptime(change_date.text(), '%d/%m/%Y')
n_months = date_difference(change_date_value, previous_date)
total_months += n_months
change_rate_value = float(change_rate.text()) / (100 * 12)
if not n_months > 0:
qtw.QMessageBox.critical(
self, 'Warning', 'Please ensure dates are in the correct order.'
)
return
rate_change_list.append((n_months, rate_value))
rate_value = change_rate_value
previous_date = change_date_value
rate_change_list.append((0, rate_value))
if not filename[0]:
return
try:
mortgage_value = int(self.ui.mortgage_input.text())
interest_rate = float(self.ui.initial_interest_input.text()) / (100 * 12)
term_length_base = int(self.ui.base_full_term_input.text())
term_length_second = int(self.ui.second_scen_full_term_input.text())
if self.ui.interest_type_box.currentText() == 'PIO':
IO_term_length_base = int(self.ui.base_IIOT_input.text())
IO_term_length_second = int(self.ui.second_scen_IIOT_input.text())
except ValueError:
qtw.QMessageBox.critical(
self, 'Warning', 'Please ensure all information is put in correctly'
)
return
if self.ui.interest_type_box.currentText() == 'ANN':
interest_paid_base = annuity_total(mortgage_value, interest_rate, term_length_base, rate_change_list) - mortgage_value
interest_paid_second = annuity_total(mortgage_value, interest_rate, term_length_second, rate_change_list) - mortgage_value
elif self.ui.interest_type_box.currentText() == 'IOM':
interest_paid_base = interest_only_total(mortgage_value, interest_rate, term_length_base, rate_change_list) - mortgage_value
interest_paid_second = interest_only_total(mortgage_value, interest_rate, term_length_second, rate_change_list) - mortgage_value
elif self.ui.interest_type_box.currentText() == 'PIO':
interest_paid_base = partial_interest_only_total(mortgage_value, interest_rate, term_length_base, IO_term_length_base, rate_change_list) - mortgage_value
interest_paid_second = partial_interest_only_total(mortgage_value, interest_rate, term_length_second, IO_term_length_second, rate_change_list) - mortgage_value
base_minus_second = interest_paid_base - interest_paid_second
labels = [
'Mortgage Value',
'Initial Interest Rate',
'Base Term Length',
'Second Scenario Term Length',
'Interest Paid Base',
'Interest Paid Second',
'Difference'
]
data = [
mortgage_value,
100 * 12 * interest_rate,
term_length_base,
term_length_second,
interest_paid_base,
interest_paid_second,
base_minus_second,
]
new_rate_list = [(self.ui.date_input.date().toString('dd/MM/yyyy'), 100 * 12 * interest_rate)]
for i in range(n_rows):
change_date = self.ui.rate_changes_table.item(i, 0)
change_rate = self.ui.rate_changes_table.item(i, 1)
if change_date is not None and change_rate is not None:
new_rate_list.append((change_date.text(), change_rate.text()))
write_to_file(filename[0], labels, data, new_rate_list)